196 citations · 910 across the 20 of their papers we have counts for
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cs.LG2019★ 69 cited
Learning to Generalize from Sparse and Underspecified Rewards
Rishabh Agarwal, Chen Liang, Dale Schuurmans +1
We consider the problem of learning from sparse and underspecified rewards, where an agent receives a complex input, such as a natural language instruction, and needs to generate a…
cs.LG2019★ 196 cited
The Evolved Transformer
David R. So, Chen Liang, Quoc V. Le
Recent works have highlighted the strength of the Transformer architecture on sequence tasks while, at the same time, neural architecture search (NAS) has begun to outperform human…